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Fareez M
@fareez541
Set up private local AI or tune your OWN GPU workstation
Vereinigte Staaten
Spanisch
Über mich
Systems engineer specializing in private, turnkey local AI infrastructure. I deploy, optimize, and benchmark fully offline AI environments—including Ollama, vLLM, ComfyUI, Open WebUI, and multi-agent workflows—fine-tuned for your exact hardware across Linux and Windows.
With a background rooted in high-reliability systems and precision workflows, I prioritize data privacy, zero-leak local storage, and maximum VRAM efficiency. No recurring API fees, no cloud surveillance—just fast, secure local compute tailored to your needs. Let's get your setup running.
I am a RN and doing this as a hobby.
Kompetenzen
Fareez M
offline •
Durchschnittliche Antwortzeit: 21 Stunden
Meine Dienstleistungen
KI-Implementierung und -Bereitstellung
I will set up private local ai or tune your amd radeon GPU workstation
Portfolio
Arbeitserfahrung
Private Local AI Deployment & Hardware-Optimized Workflows
Self Employed
Jan 2026 - Present • 10 mos
Tired of unpredictable cloud API costs, data privacy concerns, and driver conflicts? I set up, tune, and harden private, offline AI workstations and servers that extract every ounce of performance from your existing hardware. Whether you are running consumer GPUs or dedicated multi-GPU workstations, I eliminate installation headaches, resolve driver/runtime mismatches, and deliver an intuitive, browser-accessible interface ready for production work on day one. Core Capabilities Local LLM Engines & APIs: Turnkey deployment of Ollama, vLLM, SGLang, and llama.cpp with OpenAI-compatible endpoints. Interfaces & Frontends: Clean setups of Open WebUI, LibreChat, and custom local dashboards with user authentication and document management (RAG). Creative AI Pipelines: Stable Diffusion and Flux installations via ComfyUI or Automatic1111, configured with custom nodes, LoRAs, and control nets. Agent Frameworks & Automation: Orchestration setups for autonomous agents, tool-calling pipelines, and local embedding models. Hardware & Runtime Optimization: Driver configuration, VRAM allocation tuning, context window optimization, and quantization matching (GGUF, AWQ, EXL2) across Linux and Windows environments. Why Clients Trust My Work Total Data Privacy: Your machine, your data. I configure your tools strictly for offline/local execution with zero unauthorized telemetry or external dependencies. Stress-Tested Reliability: I do not simply run an installer script and log off. Every deployment is benchmarked under load to confirm thermal stability, VRAM headroom, and token throughput. Structured Handoff & Documentation: You receive clear, step-by-step documentation on how to update models, manage storage, and restart services without breaking dependencies. Transparent Communication: If your hardware cannot realistically run a specific model or quantization level, I tell you up front and recommend the optimal compromise.
